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Background: Multiple myeloma (MM) is a hematological malignancy characterized by the abnormal proliferation of plasma cells. Mitochondrial dysfunction and dysregulated programmed cell death (PCD) pathways have been implicated in MM pathogenesis. However, the precise roles of mitochondria-related genes (MRGs) and PCD-related genes (PCDRGs) in MM prognosis remain unclear. Methods: Transcriptomic data from MM patients and healthy controls were analyzed to identify differentially expressed genes (DEGs). Candidate genes were selected by intersecting DEGs with curated lists of MRGs and PCDRGs. Univariate Cox, least absolute shrinkage and selection operator (LASSO), multivariate Cox, and stepwise regression analyses identified prognostic genes among the candidates. A risk model was constructed from these genes, and patients were stratified into high- and low-risk groups for survival analysis. Independent prognostic factors were incorporated into a nomogram to predict MM patient outcomes. Model performance was evaluated using calibration curves, receiver operating characteristic (ROC) analysis, and decision curve analysis (DCA). Finally, associations between prognostic genes and immune cell infiltration/drug responses were explored. Results: 2,192 DEGs were detected between MM and control samples. 30 candidate genes were identified at the intersection of DEGs, 1,136 MRGs, and 1,548 PCDRGs. TRIAP1, TOMM7, PINK1, CHCHD10, PPIF, BCL2L1 , and NDUFA13 were selected as prognostic genes. The risk model stratified patients into high- and low-risk groups with significantly different survival probabilities. Age, gender, ISS stage, and risk score were independent prognostic factors. The nomogram displayed good calibration and discriminative ability (AUC) in predicting survival, with clinical utility demonstrated by DCA. 9 immune cell types showed differential infiltration between MM and controls, with significant associations to risk scores and specific prognostic genes. 57 drugs, including nelarabine and vorinostat, were predicted to interact with the prognostic genes. Ultimately, qPCR in clinical samples from MM patients and healthy donors validated the expression levels of the seven key prognostic genes, corroborating the bioinformatic findings. Conclusion: Seven genes (TRIAP1, TOMM7, PINK1, CHCHD10, PPIF, BCL2L1, NDUFA13) involved in mitochondrial function and PCD pathways were identified as prognostic markers in MM. These findings provide insights into MM biology and prognosis, highlighting potential therapeutic targets. [ABSTRACT FROM AUTHOR]

Introduction: Circular RNAs (circRNAs) are a novel class of RNAs which occupy gene expression at the transcriptional or post-transcriptional level, involve in many physiological processes, and participate in many diseases, especially in cancer. Our previous study showed 1 altered circRNA named circ-anaphase promoting complex subunit 7 (ANAPC7) that was upregulated in acute myeloid leukemia (AML). To further clear the expression and clinical significance of circ-ANAPC7, we enlarged the sample size and illuminated the diagnostic and monitoring value of circ-ANAPC7 in AML. Methods: Real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR) was supposed to confirm the expression of circ-ANAPC7 of AML patients. We assessed the correlation of circ-ANAPC7 and clinical variables using the Spearman correlation test. The receiver operating characteristic (ROC) curve was carried out to evaluate the diagnostic value. Results: Circ-ANAPC7 was first found to be upregulated in AML, and its expression was correlated to white blood cell counts in peripheral blood and blast percentage in bone marrow. ROC curve analysis revealed that circ-ANAPC7 has a significant value of auxiliary AML diagnosis (area under the curve = 0.915, p < 0.001). Furthermore, the expression level of circ-ANAPC7 was changed accompanied with disease condition transformation. Conclusion: Circ-ANAPC7 was upregulated in newly diagnosed and relapsed AML. It may serve as potential biomarkers for AML patient's diagnosis and monitoring. [ABSTRACT FROM AUTHOR]